Data Analytics for Admittance Matrix Estimation of Poorly Monitored Distribution Grids

Pedro C. Leal, Diogo M. V. P. Ferreira and Pedro M. S. Carvalho ()
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Pedro C. Leal: Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal
Diogo M. V. P. Ferreira: Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal
Pedro M. S. Carvalho: Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal

Energies, 2022, vol. 15, issue 23, 1-9

Abstract: Smart grid operations require accurate information on network topology and electrical equipment parameters. This paper proposes estimating such information with data from the smart grid. Assuming that the availability of bus voltage data is restricted to their magnitude, a linear model of the relationship between these data and the parameters of the admittance matrix is derived in a way that does not involve bus voltage angles. A regression optimizer is then proposed to minimize the deviation between data and values estimated by the linear model. Results on the IEEE 33 bus system are presented to illustrate the model accuracy and efficiency when used to estimate parameters of medium-voltage, three-phase balanced grids.

Keywords: data-driven; smart meter; admittance matrix; smart grids; inverse power flow (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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